Title :
A framework for modeling the appearance of 3D articulated figures
Author :
Sidenbladh, Hedvig ; De La Torre, Fernando ; Black, Michael J.
Author_Institution :
CVAP, R. Inst. of Technol., Stockholm, Sweden
Abstract :
This paper describes a framework for constructing a linear subspace model of image appearance for complex articulated 3D figures such as humans and other animals. A commercial motion capture system provides 3D data that is aligned with images of subjects performing various activities. Portions of a limb´s image appearance are seen from multiple views and for multiple subjects. From these partial views, weighted principal component analysis is used to construct a linear subspace representation of the “unwrapped” image appearance of each limb. The linear subspaces provide a generative model of the object appearance that is exploited in a Bayesian particle filtering tracking system. Results of tracking single limbs and walking humans are presented
Keywords :
face recognition; filtering theory; image representation; principal component analysis; tracking; user interfaces; 3D articulated figures; 3D data; Bayesian particle filtering tracking; HCI; limb image; linear subspace representation; modeling; motion capture system; unwrapped image appearance; walking humans; weighted principal component analysis; Animals; Bayesian methods; Biological system modeling; Ear; Electrical capacitance tomography; Filtering; Humans; Nonlinear filters; Particle tracking; Principal component analysis;
Conference_Titel :
Automatic Face and Gesture Recognition, 2000. Proceedings. Fourth IEEE International Conference on
Conference_Location :
Grenoble
Print_ISBN :
0-7695-0580-5
DOI :
10.1109/AFGR.2000.840661
